Current Issue : October-December Volume : 2022 Issue Number : 4 Articles : 5 Articles
Purpose. Pancreatic cancer (PC) is a common, highly lethal cancer with a low survival rate. Autophagy is involved in the occurrence and progression of PC. This study aims to explore the feasibility of using an autophagy-related long noncoding RNA (lncRNA) signature for assessing PC patient survival. Methods. We obtained RNA sequencing and clinical data of patients from the TCGA website. Autophagy genes were obtained from the Human Autophagy Database. The prognostic model, generated through univariate and multivariate Cox regression analyses, included 10 autophagy-related lncRNAs. Receiver operating characteristic (ROC) curves and forest plots were generated for univariate and multivariate Cox regression analyses, to examine the predictive feasibility of the risk model. Gene set enrichment analysis (GSEA) was used to screen enriched gene sets. Results. Twenty-eight autophagy-related lncRNAs were filtered out through univariate Cox regression analysis (P < 0.001). Ten autophagy- related lncRNAs, including 4 poor prognosis factors and 6 beneficial prognosis factors, were further screened via multivariate Cox regression analysis. The AUC value of the ROC curve was 0.815. GSEA results demonstrated that cancer-related gene sets were significantly enriched. Conclusion. A signature based on ten autophagy-related lncRNAs was identified. This signature could be potentially used for evaluating clinical prognosis and might be used for targeted therapy against PC....
Background: A genome-wide association study (GWAS) correlates variation in the genotype with variation in the phenotype across a cohort, but the causal gene mediating that impact is often unclear. When the phenotype is protein abundance, a reasonable hypothesis is that the gene encoding that protein is the causal gene. However, as variants impacting protein levels can occur thousands or even millions of base pairs from the gene encoding the protein, it is unclear at what distance this simple hypothesis breaks down. Results: By making the simple assumption that cis-pQTLs should be distance dependent while trans-pQTLs are distance independent, we arrive at a simple and empirical distance cutoff separating cis- and trans-pQTLs. Analyzing a recent large-scale pQTL study (Pietzner in Science 374:eabj1541, 2021) we arrive at an estimated distance cutoff of 944 kilobasepairs (95% confidence interval: 767–1,161) separating the cis and trans regimes. Conclusions: We demonstrate that this simple model can be applied to other molecular GWAS traits. Since much of biology is built on molecular traits like protein, transcript and metabolite abundance, we posit that the mathematical models for cis and trans distance distributions derived here will also apply to more complex phenotypes and traits....
Background. Mitochondria play an important role in breast cancer (BRCA). We aimed to build a prognostic model based on mitochondria-related genes. Method. Univariate Cox regression analysis, random forest, and the LASSO method were performed in sequence on pretreated TCGA BRCA datasets to screen out genes from a Gene Set Enrichment Analysis, Gene Ontology: biological process gene set to build a prognosis risk score model. Survival analyses and ROC curves were performed to verify the model by using the GSE103091 dataset. The BRCA datasets were equally divided into high- and low-risk score groups. Comparisons between clinical features and immune infiltration related to different risk scores and gene mutation analysis and drug sensitivity prediction were performed for different groups. Result. Four genes, MRPL36, FEZ1, BMF, and AFG1L, were screened to construct our risk score model in which the higher the risk score, the poorer the prognosis. Univariate and multivariate analyses showed that the risk score was significantly associated with age, M stage, and N stage. The gene mutation probability in the high-risk score group was significantly higher than that in the low-risk score group. Patients with higher risk scores were more likely to die. Drug sensitivity prediction in different groups indicated that PF-562271 and AS601245 might be new inhibitors of BRCA. Conclusion. We developed a new workable risk score model based on mitochondria-related genes for BRCA prognosis and identified new targets and drugs for BRCA research....
Background: Epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) provide a better prognosis in EGFR-mutant non-small cell lung cancer (NSCLC). Nevertheless, the outcome of leptomeningeal metastasis (LM) remains poor. In addition, due to limited access to intracranial tumour tissue, gene alterations associated with leptomeningeal metastasis from lung adenocarcinoma (LM-LUAD) are unclear. Methods: Forty-five patients with LM-LUAD from May 2019 to June 2021 in Guangdong Sanjiu Brain Hospital were enrolled in this study. Seventy-five percent (34/45) of patients with LM harbored EGFR mutations, and patients with progressive disease (PD) of LM had 3rd-generation EGFR-TKI therapy and were defined as Cohort 1; those without 3rd-generation EGFR-TKI therapy were defined as Cohort 2. Next-generation targeted panel sequencing (NGS) was performed in each cerebrospinal fluid (CSF) sample of the two cohorts, and 9/45 LM-LUAD patients had matched plasma (PLA). Results: The common gene alterations discovered in the CSF of LM-LUAD were EGFR mutation (34/45, 75%), TP53 (25/45, 56%), CDKN2A (9/45, 20%), ALK (7/45, 16%), CTNNB1 (6/45, 13%), MET (5/45, 11%), APC (4/45, 9%), FGF4 (4/45, 9%), FGF3 (4/45, 9%), ERBB2 (4/45, 9%), and PIK3CG (4/45, 9%). Cooccurring mutations of TP53 and EGFR were found in 49% (22/45) of patients and correlated with poor prognosis. CDKN2A was identified in 20% (9/45) of patients and presented slightly shorter overall survival (OS) than those without (7.1 versus 8.8 months, p = 0.2). Cohort 1 had more genes associated with poor prognosis, consisting of CDK4, CDKN2A, PIK3CG, or PIK3CA, and YES1 and MET were more likely to be detected in cohort 2. The alteration of EGFR was comparable between CSF and matched PLA. Incidences of gene alterations such as CDK4, CDKN2A, MET, SOX2, JAK2, BRAF, and PIK3CG were more likely to be identified in CSF. All mutant allele frequencies (MAF) were much higher in CSF than in matched PLA. Conclusions: CSF could be a potential candidate for the genetic profiling of LM-LUAD, demonstrating the genetic characteristics of LM in EGFR-mutated lung adenocarcinoma on diverse EGFR-TKI therapies....
MicroRNAs are post-transcriptional regulators of gene expression, and disturbances of their expression are the basis of many pathological states, including cancers. The miRNA pattern in the context of tumor microenvironment explains mechanisms related to cancer progression and provides a potential target of modern therapies. Here we show the miRNA pattern in renal cancer focusing on hypoxia as a characteristic feature of the tumor microenvironment and dysregulation of PTEN, being a major tumor suppressor. Methods comprised the CRSPR/Cas9 mediated PTEN knockout in the Renca kidney cancer cell line and global miRNA expression analysis in both in vivo and in vitro (in normoxic and hypoxic conditions). The results were validated on human cancer models with distinct PTEN status. The increase in miR-210-3p in hypoxia was universal; however, the hypoxia-induced decrease in PTEN was associated with an increase in miR-221-3p, the loss of PTEN affected the response to hypoxia differently by decreasing miR-10b-5p and increasing miR-206-3p. In turn, the complete loss of PTEN induces miR-155-5p, miR-100-5p. Upregulation of miR-342-3p in knockout PTEN occurred in the context of the whole tumor microenvironment. Thus, effective identification of miRNA patterns in cancers must consider the specificity of the tumor microenvironment together with the mutations of key suppressors....
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